Browse by author
Lookup NU author(s): Dr Ayon MukherjeeORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025 The Author(s). Biometrical Journal published by Wiley-VCH GmbH. Phase I dose escalation trials in oncology generally aim to find the maximum tolerated dose. However, with the advent of molecular-targeted therapies and antibody drug conjugates, dose-limiting toxicities are less frequently observed, giving rise to the concept of optimal biological dose (OBD), which considers both efficacy and toxicity. The estimand framework presented in the addendum of the ICH E9(R1) guidelines strengthens the dialogue between different stakeholders by bringing in greater clarity in the clinical trial objectives and by providing alignment between the targeted estimand under consideration and the statistical analysis methods. However, there is a lack of clarity in implementing this framework in early-phase dose optimization studies. This paper aims to discuss the estimand framework for dose optimization trials in oncology, considering efficacy and toxicity through utility functions. Such trials should include pharmacokinetics data, toxicity data, and efficacy data. Based on these data, the analysis methods used to identify the optimized dose/s are also described. Focusing on optimizing the utility function to estimate the OBD, the population-level summary measure should reflect only the properties used for estimating this utility function. A detailed strategy recommendation for intercurrent events has been provided using a real-life oncology case study. Key recommendations regarding the estimand attributes include that in a seamless phase I/II dose optimization trial, the treatment attribute should start when the subject receives the first dose. We argue that such a framework brings in additional clarity to dose optimization trial objectives and strengthens the understanding of the drug under consideration, which would enable the correct dose to move to phase II of clinical development.
Author(s): Mukherjee A, Moscovici JL, Liu Z
Publication type: Article
Publication status: Published
Journal: Biometrical Journal
Year: 2025
Volume: 67
Issue: 5
Print publication date: 01/10/2025
Online publication date: 10/09/2025
Acceptance date: 14/08/2025
Date deposited: 30/09/2025
ISSN (print): 0323-3847
ISSN (electronic): 1521-4036
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1002/bimj.70072
DOI: 10.1002/bimj.70072
Data Access Statement: Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
PubMed id: 40931383
Altmetrics provided by Altmetric
